Hadoop Administration Interview Questions

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Q: What makes Hadoop an ideal choice for programmers’ according to you?
Hadoop comes with many pros. It has been observed that it offer some of the best benefits of the programmers as compared with any other framework. It makes it easy for programmers to write the code reliably and detect the same errors in same. It is purely based on Java and thus there are no compatibility issues. As far as the matter of functions and distribute systems is concerned, Hadoop has become the number one choice of several programmers all over the world. In addition to this, handling bulk data very easily is another good thing about this framework.

Q: What exactly do you know about the “Big Data” in the Hadoop?
Relational database management tools often fail to perform their tasks and some stages. This is common when they have to handle a large amount of data. Big data is nothing but an array of complex data sets. It is actually an approach that makes it easy for businesses to get the maximum information from their data by properly searching, analyzing, sharing, transferring, capturing, as well as visualizing the same.

Q: Name the 5 Vs which are associated with the Hadoop Framework?
These are:
1. Velocity
2. Veracity
3. Velocity
4. Value

Q: What exactly do you know about the Hadoop Components? Tell why they are significant.
Hadoop is basically an approach that makes it easy for the users to handle big data without facing any problem. All the business decisions can simply be made by getting the most useful information in no time. Hadoop has been equipped with some of the best components that make it easy for the users to keep up the pace even if the data is too large. Hadoop has been equipped with two prime components and they are:

Q: Where exactly the Data is stored in the Hadoop in a distributed environment? On what topology does it based on?
Hadoop has a powerful data storage unit which is tagged as “Hadoop Distributed File System”. Any form of data can easily be stored in it in the form of blocks. It makes use of master and slave topology. In case the need of extended storage is felt, the same can be extended to fulfill the same. Hadoop is best in this aspect.

Q: What is name Name and Master Node in the Hadoop?
These are actually related to storage in the Hadoop. Name Node is basically considered as a master node and is responsible for maintaining the Meta data information which is related to different blocks based on some of the factors related with them. Data Nodes are considered as Slave Nodes which is mainly responsible for storage and management of data in the basic format.

Q: What exactly do you know about the Resource and Node Manager in the Hadoop Framework?
Both Resource and Node Manager are associated with the YARN. Resource Manager is responsible for receiving the requests related to data processing. It then passes the same to the parallel Node Managers and ensures the processing has been taken place in a proper manner. On the other side Node Manager make sure the proper execution of task on every single Data Node.

Q: Which node is responsible for storing and modifying the FSImage in the Hadoop technology?
The Secondary Name Node is responsible for this. It generally performs this task with the help of other parallel nodes and make sure that the task has been processed at its level best. It also generated the reports related to same which are sent along with the data for the analysis of same in the step wise manner.

Q: What do you mean by NAS? Compare it with HDFS
NAS stands for Network-attached Storage and is generally regarded as the storage server which is file-level. It is connected with a server and is mainly responsible to make sure that the access has been provided to a group of users. When it comes to storing and accessing the files, all the responsibilities are beard by the NAS which can be a software, or a hardware. On the other side, HDFS is a distributed file system and is actually based on commodity hardware.

Q: In the Hadoop technology, data can be stored in two different manners. Explain them and which one you prefer
Well, it is possible to store data in a distributed manner among all the machines within a cluster. Another approach is to choose a dedicated machine for the same. Distributed approach is a good option because failure of one machine doesn’t interrupt the entire functionality within an organization. Although back up can be created for the first case, accessing the backup data and bringing it into the main server can create a lot of time issues. Thus second option is a good one. It is reliable. However, all the machines within a cluster need to be protected in every aspect in case of confidential data or information.

Q: Can you compare HDFS and Relational Database Management System and bring some key differences?
When it comes to Hadoop, it really doesn’t matter whether the data that needs to be stored is structured, unstructured or semi-structured. Also, the schema of data is totally unfamiliar to the Hadoop. On the other side, RDBMS always have structured data. It cannot process the others. The schema of same is always known to it. When it comes to processing capabilities, RDMS has limited number of options while Hadoop enables the same without any strict upper limit on the same. Another key difference is Hadoop is open source, while the RDBMS is licensed.

Q: When the Schema validation is done in the Hadoop approach?
It is done mainly after the loading of the data. Sometime it even leads to bugs but that can be managed at a later stage. Actually, it follows the scheme on read protocol.

Q: For what purpose Hadoop is a good option to consider and Why?
Hadoop is a good option to consider for OLAP systems, data discovery, as well as for Data Analysis. Hadoop has features that make the bulk data handling very easy. Because all these tasks have a lot of data to handle, the Hadoop approach can easily be trusted.

Q: What are the benefits of Hadoop 2 over Hadoop 1?
Both are good enough to be trusted. However, some features of Hadoop 2 make it an ideal choice to consider over the Hadoop 1. One of the leading reasons is with 2, it is possible to run multiple applications at the same time without any issue which was not possible in earlier version. Also, the data handling abilities of Hadoop 2 is better and in fact quicker than the 1. In addition to this, processing takes place through a Resource Manager that always makes sure of error free results.

Q: In which architecture Active and Passive Name Nodes are present and what role did they play?
They both are available in HA i.e. High Availability architecture. Active Node runs in the cluster. Secondary Node is nothing but actually a secondary Node that is considered only when the Active is not present. It is because of no other reason than this, the passive has same data as active. It can also be considered as a back for the data available in Active.

Q: Is it possible to add or remove nodes in a Hadoop Cluster?
Yes, this can simply be done. It is one of the prime tasks of a Hadoop administrator.
18. Can multiple clients access the similar files in the HDFS?
HDFC only supports the exclusive writers. In case one client is already accessing a file and a request from another client came to access the same. The HDFS reject the request until the task of first client already accessing a file is completed.

Q: What if the Data Nodes fail? How can Name Node take its place in Hadoop?
A signal is periodically sent to the Name Node by the Data Node. This is actually a signal that represents all is fine with the Data Node. In case no signal is received, it is considered as dead. Using the replicas created, the Name Node replaces the Data Node. However, there is not always a need to replace the whole data. Only the failed blocks can be considered.

Q: What exactly do you know about a Checkpoint? Which Name Node is responsible for performing the same?
The process of modifying FSImages is considered as checkpoint or checkpointing for the FSImages. This is actually an operation that always makes sure of saving of time during the operations. It is performed by the Secondary Name Node.

Q: What is the default replication factor when the Name Node replicates the data to other nodes? Is it possible to change the same?
The default replication factor is 3. Yes, it can be changed as per need.

Q: Among the Name and Data Node, which one according to you have high memory space and Why?
Name Node only store meta data which is related to the different blocks and because of this reason it needs high memory space. Data Nodes don’t need large memory space.

Q: Suppose you have two situations and they are having small amount of data distributed across different files and a large amount of data in one file. In which situation you will use HDFS
Well, the HDFS works more reliably with the large data when the same is stored on a single file. In Name Node, the concerned information is available in the RAM and thus it cannot deal with large number of files. In case files are more, there will be large amount of Meta data it needs to deal with. It is almost impossible to store such a large volume of Meta data in the RAM.

Q: What do you mean by the term “Block” in the Hadoop?
A block is nothing but a general location which is smaller unit of a prime storage location. This is because HDFS store data in block form. It can also be considered as independent unit.

Q: What exactly is the function of jps command in Hadoop?
Hadoop daemons must remain active all the time during a process is going on. Their failure causes a lot of challenges and issues. Jps Command is used to check whether they are working properly or not.

Q: What is Rack Awareness?
It is basically an algorithm that guides the Name Node on how the blocks are to be stored. Its main aim is to put a limit on the traffic in the network. It also manages and controls the replicas of each block.

Q: How will you handle the issue of frequent crashing of Data Node in case it declares its presence due to some reason?
Hadoop can easily utilize the commodity hardware which makes it easy for the users to add or to remove data node in case the same crashes too frequently. They can easily be scaled in case data grow at a very quick rate.

Q: What is the general limit on Meta-Data for a file, a directory, or a block that need to be stored on a Name Node?
A general rule is that it shouldn’t exceed150 bytes for the proper functioning of the Name Node.

Q: What is the default block size in Hadoop 1 and in Hadoop 2?
In Hadoop 1 it is 64 MB while the same is 128 MB in case of Hadoop 2.

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